Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Lele Qi"'
Publikováno v:
Forests, Vol 13, Iss 5, p 648 (2022)
An in-depth exploration of plant–soil interactions can improve our knowledge of the succession and evolution of forest ecosystems. To understand the coupling relationship between species diversity and soil physicochemical properties in natural seco
Externí odkaz:
https://doaj.org/article/f181486e717540948d30ab5c5cb04e80
Autor:
Liantuan Xiao, Yan Gao, Chengbing Qin, Liang Wu, Shanxia Bao, Lele Qi, Shuangping Han, Guofeng Zhang, Xilong Liang, Qiang Wang
Publikováno v:
Carbon Letters. 30:123-132
Carbonaceous materials are considered as potential adsorbents for organic dyes due to their unique structures which provide high aspect ratios, hydrophobic property, large efficient surface area, and easy surface modification. In this work, graphene
Publikováno v:
Mechanical Systems and Signal Processing. 99:921-929
Gear pump is the most widely used volume type hydraulic pump, and it is the main power source of the hydraulic system. Its performance is influenced by many factors, such as working environment, maintenance, fluid pressure and so on. It is different
Publikováno v:
Safety and Reliability – Theory and Applications.
Publikováno v:
Nano-Micro Letters, Vol 12, Iss 1, Pp 1-11 (2020)
Abstract In this paper, we present a facile approach to enhance the efficiency and stability of perovskite solar cells (PSCs) by incorporating perovskite with microporous indium-based metal–organic framework [In12O(OH)16(H2O)5(btc)6]n (In-BTC) nano
Externí odkaz:
https://doaj.org/article/40f2867dd7ea42e4be19c620b5d0fa30
Publikováno v:
IEEE Access, Vol 8, Pp 13769-13780 (2020)
The intelligent transportation system in big data environment is the development trend of future transportation system, which effectively integrates advanced information technology, data communication transmission technology, electronic sensor techno
Externí odkaz:
https://doaj.org/article/157cdd067057423f9c14f705ebc3e11c
Publikováno v:
Tehnički Vjesnik, Vol 25, Iss 2, Pp 528-535 (2018)
In order to improve the accuracy and real-time performance of abnormal behaviour identification in massive video monitoring data, the authors design intelligent video technology based on convolutional neural network deep learning and apply it to the
Externí odkaz:
https://doaj.org/article/c84bec1270b148309f90ba18b345b42f
Autor:
Lele Qin, Lihua Kang
Publikováno v:
Tehnički Vjesnik, Vol 25, Iss 5, Pp 1429-1436 (2018)
Video behaviour recognition and semantic recognition understanding are important components of intelligent video analytics. Traditionally, human behaviour recognition has met problems of low recognition efficiencies and poor accuracies. For example,
Externí odkaz:
https://doaj.org/article/dc4609fea54d4f038b2a9eef8e1c5cf9
Publikováno v:
Canadian Journal of Remote Sensing, Vol 43, Iss 3, Pp 244-255 (2017)
Multi-day vegetation index (VI) composite images, the basis for crop yield estimation, are subject to temporal information losses. Using the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from Landsat_5_TM and Lands
Externí odkaz:
https://doaj.org/article/722e5fd2b3ae404cb6a208a9f5ef43fb
Autor:
Jiuyi Li, Lele Qin, Lei Zhao, Aimin Wang, Yong Chen, Liao Meng, Zhongguo Zhang, Xiujun Tian, Yanmei Zhou
Publikováno v:
International Journal of Photoenergy, Vol 2015 (2015)
Biologically treated leachate usually contains considerable amount of refractory organics and trace concentrations of xenobiotic pollutants. Removal of refractory organics from biologically treated landfill leachate by a novel microwave discharge ele
Externí odkaz:
https://doaj.org/article/2fb8ed742705445085ce337be429a50e